For detecting a human condition whether he/she is in the active state (wakeful state or awakening state) or in the sleep state, conventionally, a brain wave measurement and a pattern analysis on the brain wave are conducted. However, the brain wave measurement has to be conducted under conditions limiting a person's normal movement, for instance, a brain wave electrode and/or an eletrooculographic electrode is/are required to be set on a head of a subject, and so forth. Therefore, when operating a vehicle such as an automobile, a train, and the like, it is difficult to evaluate the human condition without imposing a strain on the subject.
Meanwhile, as a traffic accident prevention measure, a monitoring of the human condition (psychosomatic condition) of a driver in operation is receiving attention in recent years. For instance, techniques for monitoring the human condition using a heart beat or a pulse are proposed in patent document 1 (Japanese Patent Application Laid-Open No. Hei 9-308614) and patent document 2 (Japanese Patent Application Laid-Open No. Hei 10-146321). According to the techniques disclosed in patent documents 1 and 2, no large-scale setting of equipment is required for measuring brain wave, whereby facilitating the evaluation of the human condition of the driver.
The devices disclosed in patent documents 1 and 2 both determine a psychosomatic condition of the driver using a chaos indicator calculated from the heart beat or the pulse. Specifically, they are structured to calculate a Lyapunov exponent from the heart beat or the pulse, as one chaos indicator, and when the Lyapunov exponent shows, in its time-series change, a decline beyond a prescribed time, it is determined to be just before falling asleep (a state feeling drowsy) due to a stress suffered and at a level requiring a rest. It is already disclosed in Japanese Patent Application Laid-Open No. Hei 4-208136 that the chaos indicator of a bio-signal enables objective diagnosis of a human condition. It is therefore presumable that the devices disclosed in patent documents 1 and 2 are capable of detecting the state just before falling asleep.
However, in patent documents 1 and 2, the disclosure is made for the determination of a fatigue state feeling drowsy only by the chaos indicator such as a Lyapunov exponent and the like, in which, in an attempt to determine the fatigue state feeling drowsy, a process reaching to a psychologically stabilized state is detected based on the declining change of the Lyapunov exponent, and in which the heat beat or the pulse measured is processed only for the chaos indicator.
Generally, a physical capability can be divided into that for survival, which is required for maintaining a life, and that for activity, which is supported by the former. The physical capability for survival corresponds to a capability to maintain life and health, and is referred to as defensive physical capability, while the physical capability for activity is a behavioral physical capability for moving a body, and is generally understood as athletic ability. A function for supporting the physical capability for activity includes an energy generation system, an energy supply system, and an energy control system. The energy generation system functions for a muscular system measured by muscular strength, staying power, and the like, which causes a muscle fatigue. The energy supply system functions for a respiration and circulatory system measured by oxygen uptake and heart rate. The energy control system functions for alterness, cooperativeness, balance, and adoptability. Consequently, the functional status of the energy generation system causing muscle fatigue can be known by analyzing the state of the energy supply system or the energy control system.
Now, by obtaining the Lyapunov exponent of a bio-signal data, the state of the energy control system can be known, and by measuring a resistance force (power value) obtainable from a peak value for each cycle of the bio-signal, the state of the energy supply system can be known. Accordingly, with the use of the Lyapunov exponent or the power value, which are obtainable from the bio-signal data, the functional status of the energy generation system can be known. However, as mentioned before, currently, only the Lyapunov exponent is paid attention, and the power value is not within the scope for understanding the functional status of the energy generation system.
For more detail, as a characteristic of a fatigue state feeling drowsy, the Lyapunov exponent sometimes shows a sharp downward trend, in other cases, a change in the power value can be seen sometimes more remarkable than the change in the Lyapunov exponent due to functional capability down of the energy supply system caused by energy release under the active state. Such a difference in change patterns largely depends on individual differences or health conditions. Therefore, for detecting an emergence of the fatigue state feeling drowsy more properly, the time-series change in the Liapunov exponent being an indicator of the state of the energy control system, and the time-series change in the power value being an indicator of the state of the energy supply system, are preferably used together in the system instead of using one.
In other words, the wakeful state or awakening state (active state) is a state psychologically stimulated and consuming higher calories, and when falling asleep, a person experiences a state psychologically relaxed but consuming still higher calories to reach to a state psychologically relaxed and consuming lower calories, or experiences a state psychologically stimulated but consuming lower calories to reach to the state psychologically relaxed and consuming lower calories. A typical sign indicating the former state psychologically relaxed but still consuming higher calories is an apparent decline in the Lyapunov exponent, and a typical sign indicating the latter state psychologically stimulated but consuming lower calories is an apparent decline in the power value. Based on this perspective, again, it is preferable to detect both the Lyapunov exponent and the power value instead of detecting one.
Further, in patent documents 1 and 2, the values of the Lyapunov exponent and the heart rate track the time-series changes thereof, while the value is detected for every 15 minutes or 30 minutes. Therefore, it is difficult to monitor the change in state substantially in real time, as required for a monitoring while driving.